Biometric sensors for mobile devices, including fingerprint sensors, are becoming increasingly smaller. A primary driving force toward smaller biometric sensors comes from the popularity of mobile electronic devices such as smart phones. Since mobile electronic devices are limited in size, components such as fingerprint sensors must also be small. Furthermore, as more components are incorporated into a mobile electronic device and the overall size of that mobile device does not increase, the components must be reduced in size in order to fit within size constraints of the mobile device.
For purposes of describing the invention, this document will focus on fingerprint sensors, but the invention is not limited to this small subset of biometric sensors. Traditional fingerprint sensors that can capture an entire finger typically have an active image area of about 1″×1″. However, capture sizes of fingerprint sensors for smart phones are generally much smaller, with active image areas on the order of about 15 mm×6 mm, 9 mm×4 mm, 8 mm×3 mm, 5 mm×5 mm, and smaller. As such, the fingerprint sensor on a smart phone or mobile device may often image only a small portion of a fingerprint (e.g. a friction-ridge surface of a finger).
Since the active area of a fingerprint sensor is often much smaller than a finger, the finger can be placed over the sensor in a variety of orientations and positions. If the fingerprint template information (also referred to as a template) generated from an acquired fingerprint image obtained during an enrollment process does not closely match the template obtained from the fingerprint at the time of inquiry, the fingerprint matching component of the mobile electronic device may fail to properly identify or verify a user. When the fingerprint matching component fails to properly verify the user, the component may falsely reject the user as being unauthorized for the desired task (which may include unlocking or otherwise using the mobile device).
It should be noted that the actual fingerprint image may not be matched to another fingerprint image. Rather, a template having information about a fingerprint may be created by a feature extraction process, and the templates may be compared to one another in order to determine whether a match exists. Matching processes may utilize, for example, minutiae-matching or pattern-matching (a.k.a. keypoint-matching) procedures. Fingerprint templates may contain information, for example, about minutiae points or keypoints within a fingerprint image.
Attempts have been made to reduce the false rejection rate. One of the more popular solutions involves obtaining multiple templates corresponding to images of the finger at the time of enrollment. During the enrollment process, the user is asked to place a finger on the fingerprint sensor repeatedly, for example, 10 to 15 times. After each placement, the user is asked to move his/her finger “slightly” before a subsequent image is taken. This “stitched enrollment” process can be frustrating for the user.
The goal of this stitching technique is to create a full size enrollment image by stitching together multiple smaller images. However, in order for this stitching technique to yield the desired benefits, the user must place his/her finger on the fingerprint sensor in such a manner as to have new ridge structure imaged by the sensor that was not previously imaged during the enrollment process, but still have enough overlap with the previous image so as to allow the fingerprint matching component to correlate the two images (i.e. stitch the images together). The desired amount of overlap does not always occur, thereby undermining the ability of the system to properly identify those who have enrolled. Improvements to the speed and accuracy of enrolling and validating a user of a mobile device are therefore desired, particularly for sensors with a smaller active area.